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8,537 results for “Openness”
Open data repository, Boehm-Sturm et al., Phenotyping placental oxygenation in Lgals1 deficient mice using 19F MRI
<p>Open data repository of journal article "Phenotyping placental oxygenation in Lgals1 deficient mice using <sup>19</sup>F MRI"</p>
Enhanced Molecular Spin-Photon Coupling at Superconducting Nanoconstrictions. Open data sets
<p>Includes data relevant for publication with DOI <a href="https://doi.org/10.1021/acsnano.0c03167">10.1021/acsnano.0c03167</a> plus a table with information on how the data were obtained and processed.</p>
Austrian Science Fund (FWF) Open Access Compliance Monitoring 2019
<p><strong>I. Executive summary</strong></p> <p>The Austrian Science Fund (FWF), which is Austria's main funding organisation for basic research, encourages and helps all project leaders and project staff members to make their peer-reviewed research results freely available on the Internet. Any exceptions must be clearly indicated and justified. For projects that started after 1 January 2015, open access has been compulsory for all peer-reviewed publications. All principal investigators in FWF-funded projects are obliged to submit a final report within three months of completing their projects.</p> <p>In 2019 all in all 565 final reports were submitted to the FWF, 44 out of them couldn't report publications by now. The publications and other data mentioned in those reports are archived and analysed by the FWF. This report examines the state of compliance with open access requirements on the basis of final project reports submitted in the year 2019.</p> <p>Main findings:</p> <p>-A total of 9.353 publications were listed in the final project reports submitted in 2019.</p> <p>-Of those publications, 7.326 were conclusively identified as peer-reviewed.</p> <p>-Regarding compliance with the FWF's Open Access Policy, the analysis shows that 89% of the peer-reviewed publications that are listed in the submitted final reports of FWF projects in 2019 are openly accessible (2015: 83%, 2016: 92%, 2017: 90%, 2018: 92%).</p> <p>-The most frequently chosen option is hybrid open access (40%). The share of old open access is 19%, the share of green open access 22% and other open access 8%.</p> <p>-The majority of peer-reviewed publications submitted are journal articles (91%), 91% of which are openly accessible.</p> <p>-The lowest rate of compliance with the FWF's Open Access Policy can be found in editions, contributions to edited volumes and monographs (42%).</p> <p>-Although open access is not compulsory for non peer-reviewed publications, 43% of those publications are freely available through the internet.</p> <p>-The absolute number of publications listed in final reports in 2019 includes 565 publications that are mentioned several times in different projects; however, those repetitions do not ultimately affect the relative share of open access publications (89%).</p> <p><strong>II. Bias</strong></p> <p>Half of the publications were entered in the FWF’s database manually and with utmost care when the final project reports were received. Nevertheless, it is not possible to rule out minor errors entirely. The other half has been submitted to the FWF via a research documentation system (provided by ©Researchfish) in which FWF-funded researchers are able to enter and update their research data on an ongoing basis. The last check of the open access status was performed in January 2020. In some cases, the embargo period may have already expired, and publications labelled other open access in the FWF’s database may now be accessible through green open access.</p> <p>Whenever the status "peer-reviewed" could not be clearly identified according to FWF guidelines, the publications were classified as non peer-reviewed.</p> <p>Openly available non peer-reviewed publications were entered as 'openly available'.</p> <p> </p>
Video: Crashkurs Digitale Langzeitarchivierung - Das Referenzmodell Open Archival Information System (OAIS)
<p>Dieser Crashkurs stellt das Referenzmodell Open Archival Information System (OAIS) vor, das die verschiedenen Tätigkeitsbereiche eines Langzeitarchivs beschreibt. Als internationaler Standard (ISO 14721) bietet das OAIS-Modell eine Kommunikationsgrundlage zum Thema der Digitalen Langzeitarchivierung. So sind zentrale OAIS-Begriffe wie Preservation Planning, Archival Information Package und Designated Community in der Langzeitarchivierungs-Community etabliert.</p> <p>In dieser Einführung werden die Aufgaben eines Digitalen Langzeitarchivs anhand der verschiedenen OAIS-Funktionseinheiten beschrieben. Ebenso bietet der Crashkurs einen Überblick über die verschiedenen Verarbeitungsstadien von Informationspaketen (SIP, AIP, DIP) in einem Langzeitarchiv.</p> <p>Dieser Crashkurs wurde als Lehrvideo für das Teil-Modul "Digitale Langzeitarchivierung" des <a href="https://www.th-koeln.de/weiterbildung/zertifikatskurs-data-librarian_63393.php">Zertifikatskurses "Data Librarian"</a> erstellt. Der Zertifikatskurs wurde 2019/2020 vom Zentrum für Bibliotheks- und Informationswissenschaftliche Weiterbildung der Technischen Hochschule Köln unter wissenschaftlicher Leitung von Prof. Dr. Konrad Förstner ausgerichtet.</p>
Figure 4 in The muscles, body wall and valve-opening mechanism of extant craniid (inarticulated) brachiopods
Figure 4. Line drawings and digital photographs illustrating cilia current flow and valve features of two species. (A) Diagram showing flow directions of dorsal mantle cilia currents. (B) Diagram of craniid valves and body (after Williams et al. 1997). (C–E) Novocrania californica. C. Cutaway drawing down midline of valves and muscle raising structures. (D, E) OU 44518a-b. Oblique photographs of dorsal and ventral valve interiors. (F–H) Novocrania japonica. (F, G) TUM 951117a. Oblique photographs of dorsal and ventral valve interiors. (H) Cutaway drawing down midline of valves and muscle raising structures. Abbreviations: a, anus; aasc, anterior adductor muscle scar; dv, dorsal valve; msp, median spike; pasc, posterior adductor muscle scar; raams, raised anterior adductor muscle scar; rp, raised pedestal; tve, thin valve extension; vmd, ventral mound; vv, ventral valve.
Covid19Kerala.info-Data: A collective open dataset of COVID-19 outbreak in the south Indian state of Kerala
<p>Covid19Kerala.info-Data is a consolidated multi-source open dataset of metadata from the COVID-19 outbreak in the Indian state of Kerala. It is created and maintained by volunteers of ‘Collective for Open Data Distribution-Keralam’ (CODD-K), a nonprofit consortium of individuals formed for the distribution and longevity of open-datasets. Covid19Kerala.info-Data covers a set of correlated temporal and spatial metadata of SARS-CoV-2 infections and prevention measures in Kerala. Static releases of this dataset snapshots are manually produced from a live database maintained as a set of publicly accessible Google sheets. This dataset is made available under the Open Data Commons Attribution License v1.0 (ODC-BY 1.0). <br> <br> <strong>Schema and data package</strong><br> Datapackage with schema definition is accessible at <a href="https://codd-k.github.io/covid19kerala.info-data/datapackage.json">https://codd-k.github.io/covid19kerala.info-data/datapackage.json</a>. Provided datapackage and schema are based on <a href="https://specs.frictionlessdata.io/data-package/">Frictionless data Data Package specification</a>.</p> <p><strong>Temporal and Spatial Coverage </strong></p> <p>This dataset covers COVID-19 outbreak and related data from the state of Kerala, India, from January 31, 2020 till the date of the publication of this snapshot. The dataset shall be maintained throughout the entirety of the COVID-19 outbreak. </p> <p>The spatial coverage of the data lies within the geographical boundaries of the Kerala state which includes its 14 administrative subdivisions. The state is further divided into Local Self Governing (LSG) Bodies. Reference to this spatial information is included on appropriate data facets. Available spatial information on regions outside Kerala was mentioned, but it is limited as a reference to the possible origins of the infection clusters or movement of the individuals. </p> <p><strong>Longevity and Provenance </strong></p> <p>The dataset snapshot releases are published and maintained in a designated GitHub repository maintained by CODD-K team. Periodic snapshots from the live database will be released at regular intervals. The GitHub commit logs for the repository will be maintained as a record of provenance, and archived repository will be maintained at the end of the project lifecycle for the longevity of the dataset.</p> <p><strong>Data Stewardship </strong></p> <p>CODD-K expects all administrators, managers, and users of its datasets to manage, access, and utilize them in a manner that is consistent with the consortium’s need for security and confidentiality and relevant legal frameworks within all geographies, especially Kerala and India. As a responsible steward to maintain and make this dataset accessible— CODD-K absolves from all liabilities of the damages, if any caused by inaccuracies in the dataset. </p> <p><strong>License </strong></p> <p>This dataset is made available by the CODD-K consortium under ODC-BY 1.0 license. The Open Data Commons Attribution License (ODC-By) v1.0 ensures that users of this dataset are free to copy, distribute and use the dataset to produce works and even to modify, transform and build upon the database, as long as they attribute the public use of the database or works produced from the same, as mentioned in the citation below. </p> <p><strong>Disclaimer </strong></p> <p>Covid19Kerala.info-Data is provided under the ODC-BY 1.0 license as-is. Though every attempt is taken to ensure that the data is error-free and up to date, the CODD-K consortium do not bear any responsibilities for inaccuracies in the dataset or any losses—monetary or otherwise—that users of this dataset may incur. </p>
RTPTorrent: An Open-source Dataset for Evaluating Regression Test Prioritization
<p>This dataset is designed to be used in evaluation studies of regression test prioritization techniques. It includes 20 open-source Java projects from GitHub and over 100,000 logs of real-world build logs from TravisCI. The projects span a wide range with regard to size, number of contributors, and maturity of open-source Java projects available on GitHub.</p> <p>Futher, the dataset includes the results of baseline approaches to ease the comparison of new techniques applied to the dataset.</p> <p>A readme file with a more detailed description of the structure of the dataset is included. For even more information see the corresponding MSR 2020 publication.</p> <p>Versions:</p> <ul> <li> 2020-09-23 (version 1.1) <ul> <li>Updated archived `deeplearning4j` repository with a fork that contains all of the original commits. Repository at the original GitHub location had been replaced. Defect identified by Daniel Elsner (Technische Universität München).</li> <li>Renamed root folder from MSR2 to rtp-torrent</li> </ul> </li> <li>2020-05-25 (version 1.0) <ul> <li>Initial release</li> </ul> </li> </ul> <p> </p>
Corresponding spreadsheet to the Paper 'An intersectional approach to analyse gender productivity and open access: a bibliometric analysis of the Italian National Research Council' submitted to the Scientometric journal by Roberta Ruggieri, Fabrizio Pecoraro and Daniela Luzi from National Research Council, Italy.
<p>Gender equality and Open Access (OA) are priorities within the European Research Area (ERA) and cross-cutting issues in European research program H2020. Gender and openness are also key elements of Responsible Research and Innovation (RRI). However, despite the common underlying targets of fostering an inclusive, transparent and sustainable research environment, both issues are analysed as independent, unrelated topics.<br> This paper represents a first exploration of the inter-linkages between gender and OA analysing the scientific production of researchers of the Italian National Research Council under a gender perspective integrated with the different OA publications modes. A bibliometric analysis was carried out for articles published in the period 2016-2018 and retrieved from the Web of Science. Results are presented constantly analysing CNR scientific production in relation to gender, disciplinary fields and OA publication modes. These variables are also used when analysing articles that receive financial support.<br> Our results indicate that gender disparities in scientific production still persist in particularly in STEM disciplines (Science, Technology, Engineering and Mathematics), while in medical and agricultural sciences the gender gap is the closest to parity. A positive dynamic toward OA publishing and women scientific production is shown when open disciplines with well-established practices are related to articles supported by funds. A slightly higher women propensity toward OA is shown when considering Gold OA,OA or authorships with women in the first and last article by-line position. Moreover, the prevalence of Italian funded articles with women’s contributions published in Gold OA journals seems to confirm this tendency, especially if considering the week enforcement of the Italian OA policies.</p>
Open Science Café
<p>Event for Berlin Science Week 2020: a series of 20 minute talks on Open Science topics by graduates of the ORION Open Science Train-the-Trainer course and guests. </p> <p>Talks: </p> <ul> <li>Open Science: A History </li> <li>Citizen Science</li> <li>‘SMOVE’: A Citizen Science Project</li> <li>Open Data</li> <li>Open myDNA: Become your own genome hacker</li> <li>Open Content and Licensing</li> <li>Open Hardware</li> <li>Open Source</li> <li>Open Access</li> <li>Science Communication</li> </ul> <p> </p>
The Corona Connection: How LabHive and Open Science is Helping Scientists Solve COVID-19
<p><strong>Episode Summary: </strong></p> <p>The Coronavirus pandemic has led to many new initiatives to help scientists share resources and data. We talked to, Tobias Opialla and Lisa Rieble who have created a new platform called LabHive. We discussed what LabHive is and how it got started, as well as how Open Science principles and practices relate to the new normal and how communication is key. </p> <p><strong>Episode Links: </strong></p> <p><a href="https://labhive.de/#/">LabHive</a></p> <p><a href="https://wirvsvirus.org/">WirVsVirus</a></p> <p><a href="https://berlin.impacthub.net/">Impact Hub Berlin</a></p> <p><strong>Bonus links regarding Drosten, the Teachers and Kindergarteners and the BILD:</strong></p> <p>Original tweet from Drosten:<br> <a href="https://twitter.com/c_drosten/status/1264934434756755456">https://twitter.com/c_drosten/status/1264934434756755456</a> </p> <p>Replies from improperly quoted reviewers:<br> <a href="https://twitter.com/jdoeschner/status/1264948078790029313">https://twitter.com/jdoeschner/status/1264948078790029313</a> <br> <a href="https://twitter.com/domliebl/status/1264935266185293826">https://twitter.com/domliebl/status/1264935266185293826</a> <br> <a href="https://twitter.com/polenz_r/status/1264946109719379970">https://twitter.com/polenz_r/status/1264946109719379970</a> <br> <a href="https://twitter.com/christoph_rothe/status/1265344225979314177">https://twitter.com/christoph_rothe/status/1265344225979314177</a> <br> <a href="https://twitter.com/christoph_rothe/status/1264930677306413058">https://twitter.com/christoph_rothe/status/1264930677306413058</a> </p> <p>The xkcd regarding preprints:<br> <a href="https://xkcd.com/2304/">https://xkcd.com/2304/</a> </p> <p>Regarding renewed interest in Testing:<br> Drosten wanting to test schools and Kindergartens<br> <a href="https://www.ndr.de/nachrichten/info/39-Welche-Chancen-neue-Tests-bieten,podcastcoronavirus206.html">https://www.ndr.de/nachrichten/info/39-Welche-Chancen-neue-Tests-bieten,podcastcoronavirus206.html</a> </p> <p>Press Release from Berlin Senate regarding test strategy:<br> <a href="https://www.berlin.de/rbmskzl/aktuelles/pressemitteilungen/2020/pressemitteilung.935676.php">https://www.berlin.de/rbmskzl/aktuelles/pressemitteilungen/2020/pressemitteilung.935676.p</a>df </p>
Three reconstructions of the formation of large open ocean polynyas in the Southern Ocean using ice core records
<p>The dataset contains the indices for three reconstructions of open ocean polynya formation in the Southern Ocean over the period 1250-1990 and their uncertainties. See the associated publication</p> <p>Goosse H., Dalaiden Q., Cavitte M.G.P., Zhang L. Can we reconstruct the formation of large open ocean polynyas in the Southern Ocean using ice core records? Climate of the past 2020. <a href="https://doi.org/10.5194/cp-2020-91">https://doi.org/10.5194/cp-2020-91</a></p> <p>The data are included in a text file. The first column is the time (in years). The next six columns are the three reconstructions using data assimilation with SPEAR_AM2 (DA AM2), using data assimilation with SPEAR_LO (DA LO) and a simple average of standardized time series (Stat), each of them directly followed by their uncertainties. The uncertainties are estimated from the standard deviation of the seven reconstructions using different combinations of the available ice core records.</p> <p>Please contact <a href="mailto:hugues.goosse@uclouvain.be">Hugues Goosse</a>(hugues.goosse@uclouvain.be) for more information.</p>
Sprint for your eLife! How the eLife Innovation Sprint Helps Drive Forward Open Science Projects
<p><strong>Episode Summary</strong></p> <p>In this episode we cover the eLife Innovation Sprint 2020, that was held online on September 2nd and 3rd, 2020. The sprint facilitates collaboration between people who are working on tools, services, and other projects that enhance open science and research.</p> <p>We talk to the organiser Dr Emmy Tsang, who at the time was the Innovation Community Manager for eLife but is now the Community Engagement Manager for TU Delft. As well as participants from two of the projects that took part: Dr Cássio Amorim, creator of SciGen.Report, 'a platform to easily share and view any information that researchers may have on the reproducibility of papers'. And Esha Datta and Daniel Nüst, who who both joined the sprint to work on the Expanding Open Grants project, developed by Dr Hao Ye, which increases accessibility to examples of grants and proposals. </p> <p><strong>Episode Links: </strong></p> <p><a href="https://sprint.elifesciences.org/">eLife Sprint</a></p> <ul> <li>Emmy Tsang: @emmy_ft </li> <li>@eLifeInnovation</li> </ul> <p><a href="https://scigen.report/">SciGen.Report</a></p> <ul> <li>@ScigenReport </li> </ul> <p><a href="https://www.ogrants.org/">Expanding Open Grants</a></p> <ul> <li>@nordholmen</li> <li>The new GH org for the sprint with latest developments:<br> <a href="https://github.com/expanding-open-grants/">https://github.com/expanding-open-grants/</a></li> <li>The wrap up slides are at:<br> <a href="https://docs.google.com/presentation/d/1PlW7Iq5xOKu1kbo_CLvnYXBJ3ldPdd4ulggZJl4F2-Y/edit#slide=id.g96e132450a_0_112">https://docs.google.com/presentation/d/1PlW7Iq5xOKu1kbo_CLvnYXBJ3ldPdd4ulggZJl4F2-Y/edit#slide=id.g96e132450a_0_112</a> </li> </ul>
Unblocking Breakthroughs: How DEIP Are Using Blockchain and Open Science to Provide Innovation Evaluation
<p><strong>Episode Summary:</strong></p> <p>In this episode we talk to Alex Shkor about his company DEIP which is a peer review platform and blockchain protocol for the evaluation of intellectual capital, research, and innovation. We discussed why Alex created this platform, what the potential for digital research and big data is, and how Open Science can accelerate research. </p> <p><strong>Episode Links: </strong></p> <p><a href="https://deip.world/">DEIP</a></p>
Know Your Research Rights: The Legal Perspective on Copyright and Open Science
<p><strong>Episode Summary:</strong></p> <p>In this episode we talk to two copyright lawyers, Malcolm Bain and Lucrezia Berto, about what the legal framework of research creation and sharing is. Who owns your research? What needs to be considered before you make it open? </p> <p><strong>Episode Links:</strong></p> <p><a href="https://acrosslegal.com/en/">Across Legal</a></p> <p><a href="https://www.linkedin.com/in/malcolm-bain-9216415/?originalSubdomain=es">Malcolm Bain</a></p> <p><a href="https://www.linkedin.com/in/lucrezia-berto/?originalSubdomain=es">Lucrezia Berto</a></p>
A Slice of the Research Cake: The Impact of Open Science in Africa
<p><strong>Episode Summary: </strong></p> <p>In this episode we talk to Joy Owango, Founding Director at Training Centre in Communication. We discussed how Open Science is democratising research and access to data and publishing in Africa, the importance of ownership in research, and the challenges inherent in widespread change. </p> <p>Originally we interviewed another two guests who are involved in the Open Science movement on the African continent: Osman Aldirdiri, founding director of Open Sudan initiative and Jo Havemann, co-founder of the AfricArXiv. Due to technical difficulties we can only publish the audio from Joy Owango. However, we do have a <a href="https://drive.google.com/file/d/1sOhAaiWjAUwQlDMuaqd5YCC3SOhXDFSP/view?usp=sharing">transcript of the full interview</a> with all three guests.</p> <p><strong>Episode Links:</strong></p> <ul> <li><a href="https://info.africarxiv.org/">AfricArXiv</a> <p><a href="https://twitter.com/AfricArxiv">Twitter</a></p> </li> <li>Joy Owango <ul> <li><a href="https://www.tcc-africa.org/">Training Centre in Communication</a></li> <li><a href="https://twitter.com/JoyOwango">Twitter</a></li> </ul> </li> <li>Osman Aldirdiri <ul> <li><a href="https://blog.okfn.org/2017/03/30/open-data-day-sudan-2017-openness-for-advancing-research-and-discovery/">Open Sudan's Open Data Day</a></li> <li><a href="https://twitter.com/aldirdiri">Twitter</a></li> </ul> </li> <li>Jo Havemann <ul> <li><a href="https://access2perspectives.com/team/jo-havemann/">Access2Perspectives </a></li> </ul> </li> </ul>
The Utopian Model: How The Neuro Has Become An Open Science Institution
<p><strong>Episode Summary:</strong></p> <p>In this episode we talk to Dylan Roskams-Edris from Open Science Alliance Officer at Tanenbaum Open Science Institute and The Neuro in Canada. We discussed how The Neuro made itself into the worlds first open neuroscience institution, the challenges and opportunities of embracing Open Science at an institutional level, how Open Science itself needs to be more open, and the potential for scientists working in such a system.</p> <p><strong>Episode Links: </strong></p> <p> <a href="https://www.linkedin.com/in/dylan-roskams-edris-26690598/?originalSubdomain=ca">Dylan Roskams-Edris</a></p> <p><a href="https://twitter.com/dylanwre?lang=en">Twitter</a></p> <ul> <li><a href="https://t.co/N3BFnpiVgv?amp=1">The Neuro</a> <ul> <li><a href="https://twitter.com/TheNeuro_MNI">Twitter</a></li> </ul> </li> </ul>
Enhancing Open Modification Searches via a Combined Approach Facilitated by Ursgal
<p>The identification of peptide sequences and their post-translational modifications (PTMs) is a crucial step in the analysis of bottom-up proteomics data. The recent development of open modification search (OMS) engines allows virtually all PTMs to be searched for. This not only increases the number of spectra that can be matched to peptides but also greatly advances the understanding of biological roles of PTMs through the identification, and thereby facilitated quantification, of peptidoforms (peptide sequences and their potential PTMs). While the benefits of combining results from multiple protein database search engines has been established previously, similar approaches for OMS results are missing so far. Here, we compare and combine results from three different OMS engines, demonstrating an increase in peptide spectrum matches of 8-18%. The unification of search results furthermore allows for the combined downstream processing of search results, including the mapping to potential PTMs. Finally, we test for the ability of OMS engines to identify glycosylated peptides. The implementation of these engines in the Python framework Ursgal facilitates the straightforward application of OMS with unified parameters and results files, thereby enabling yet unmatched high-throughput, large-scale data analysis.</p> <p>This dataset includes all relevant results files, databases, and scripts that correspond to the accompanying journal article. Specifically, the following files are deposited:</p> <ul> <li>Homo_sapiens_PXD004452_results.zip: result files from OMS and CS for the dataset PXD004452</li> <li>Homo_sapiens_PXD013715_results.zip: result files from OMS and CS for the dataset PXD013715</li> <li>Haloferax_volcanii_PXD021874_results.zip: result files from OMS and CS for the dataset PXD021874</li> <li>Escherichia_coli_PXD000498_results.zip: result files from OMS and CS for the dataset PXD000498</li> <li>databases.zip: target-decoy databases for <em>Homo sapiens</em>, <em>Escherichia coli </em>and <em>Haloferax volcanii</em> as well as a glycan database for <em>Homo sapiens</em></li> <li>scripts.zip: example scripts for all relevant steps of the analysis</li> <li>mzml_files.zip: mzML files for all included datasets</li> <li>ursgal.zip: current version of Ursgal (0.6.7) that has been used to generate the results (for most recent versions see https://github.com/ursgal/ursgal)</li> </ul>
Antwerp precipitation, open water streams and sewer system sensor data
<p>This csv dataset includes historical data for the period 2018-2020 from multiple sensors deployed in Antwerp that can help city services to have a clear view on the actual precipitation in different regions, the water level of different water flows as well as the water flows in the sewer system of the city. This data was used in CUTLER (visualized in Antwerp’s dashboard) to assist in the impact modelling of garden streets.</p> <p>The data set contains:</p> <p>- 6 water level sensors: lora.0004A30B00202D0C, lora.0004A30B00204B8B, lora.0004A30B00200BFE, lora.0004A30B0021F1D4, lora.0004A30B002041F6, lora.0004A30B001FC6DF</p> <p>- 4 pluvio meters: lora.0004A30B002025F5, lora.0004A30B00201DCC, lora.0004A30B001FF6F7, lora.0004A30B001FA140<br> <br> - 3 sewer level meters: lora.0004A30B001FD07B, lora.0004A30B0020112D, lora.0004A30B001F9B4B</p>
F.A.I.R. open dataset of brushed DC motor faults for testing of AI algorithms
<p>Practical research in AI often lacks of available and reliable datasets so the practitioners can try different algorithms. The field of predictive maintenance is particularly challenging in this aspect as many researchers don't have access to full-size industrial equipment or there is not available datasets representing a rich information content in different evolutions of faults.</p> <p>This dataset presents the evolution of typical faults (commutator, winding and brush wear) in inexpensive DC motors under extensive monitoring (vibration, temperature, voltage, current and noise). These motors exhibit a particularly short useful life when operating out of nominal conditions (from 30 minutes to 6 hours) which make them very interesting to test different signal processing algorithms and introduce students and researchers into signal processing, fault detection and predictive maintenance.</p> <p>The data-set comprises two main elements:</p> <ul> <li>A spreadsheet with the processing of each raw data file</li> <li>4 folders with raw data files in HDF5 format</li> </ul> <p>The spread sheet contains the following columns</p> <ul> <li>filename of the raw data file</li> <li>timestamp of the raw data file</li> <li>speed of the motor in rpm</li> <li>speed of the motor in Hz</li> <li>Current of the moter (A)</li> <li>Voltage supply (V)</li> <li>surface motor temperature (ºC)</li> <li>ambient temperature (ºC)</li> <li>For each measured signal (Vibration, current, voltage) the vibration of the main harmonic (at the speed of the motor) and it's first 10 multiple.</li> <li>For each measured signal (Vibration, current, voltage) the vibration in 4 bands: 0-4kHz, 4kHz-8kHz, 8kHz-16kHz, 16kHz-26kHz</li> </ul> <p>The raw data files in HDF5 format contains the instantaneous measured vibration (g), current (A) and voltage (volts) of the DC motor at 51.200 Hz.</p>
Data and MATLAB Code for the paper entitled "A modified Chezy formula for one-dimensional unsteady frictional resistance in open channel flow"
<p>This link includes the data and MATLAB code files for the research paper entitled "A modified Chezy formula for one-dimensional unsteady frictional resistance in open channel flow" by Zhou, J.W.; Bro, W.M.; Tick*, G.R.; Mofatakari, H.; Li, Y.; and Cheng, L., which has been submitted to the Journal of Fluids Engineering. These files are edited under the GB18030 character set standard.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.